The effects of automation on unemployment and mental health: Is universal basic income the ultimate cure?

Globally, mental health and substance abuse are the fifth highest reason why people miss healthy years of life. Research shows that there is a link between unemployment and financial insecurity and mental well-being.[1] Being in constant fear of losing one’s job or not having enough money to pay bills is associated with deteriorated mental well-being (Gross, 2015). Precarity in all its forms is associated with mental health problems. Technological progress a key driver for precarity. Estimates vary on how automation impacts the world of work. In the United States, data on how many jobs could be automated in the future range from 9% (OECD, 2016) to 38% (PWC, 2018). Among the research questions to be addressed in this paper are:

What is the most current research on mental health, precarity, and financial insecurity?

What is the anticipated scale of job automation in both the Global South and Global North?

This paper presents policy recommendations to find solutions that accommodate technological change in a way that benefits people. UBI and other social policy measures will be examined. Policy recommendations will take stock of the diverging contexts in different regions of the world.

Development of mental health issues globally

Regarding mental health, we need first to look at overall health. Fortunately, the health of people around the world has increased in many aspects and in most regions. Five out of seven regions have experienced tremendous gains in the overall health of their populations. High-income countries have only slightly improved their health levels since 1990, but it is fair to say that their level of health is quite advanced.

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Central and Eastern Europe and Central Asia are the only regions that have seen a steep rise in health issues since the 1990s, but are now returning to their base level. Much of this increase was probably due to the hardships people suffered in transitioning from socialism to capitalism. In the chart below, the DALYs (disability-adjusted life years) are measured. According to the World Health Organization (1999), DALY is defined as “the sum of years of potential life lost due to premature mortality and the years of productive life lost due to disability” or Disability-adjusted life year). The graph below indicates that the number of years lost to premature mortality is decreasing. This means that, overall, people are living healthier lives.

Figure 1

Based on data from the Institute for Health Metrics and Evaluation (IHME), retrieved from https://vizhub.healthdata.org/gbd-compare/.

Figure 2

Based on data from the Institute for Health Metrics and Evaluation (IHME), retrieved from https://vizhub.healthdata.org/gbd-compare/.

Intriguingly, when looking at mental health (see the chart above) the picture is quite different from overall health. Four out of seven regions in the world witnessed a substantial increase in DALY to poor mental health, while two regions (Eastern Europe and sub-Saharan Africa) saw only a slight deterioration in mental health, and one region (high-income) stabilised at a very high level. Mental health issues are no longer a ‘first-world problem’, because countries of the Global South have witnessed a sharp increase in mental health problems. Globally, depression and anxiety disorders are the most prominent types of mental health problems. The WHO acknowledges the strong impact of financial insecurity: “Management of depression should include psychosocial aspects, including identifying stress factors, such as financial problems, difficulties at work or physical or mental abuse, and sources of support, such as family members and friends” (WHO, 2018). Today, it is an established fact that unemployment, as well as the fear of losing one’s job, (even if that fear never materialises) have a negative effect on mental well-being.

Looking at the scale of mental health diseases (including substance abuse), mental health issues are now the fifth major cause for healthy years of life lost, globally. The results below were presented in a study by Whiteford et al. (2013). The chart shows the DALYs for the most common types of diseases.

Figure 3

Based on data from Whiteford et al. (2013).

Looking at mental health from an economic perspective, it is evident that mental health issues are a financial burden for all EU countries. A substantial amount of resources is spent on mental health problems in the EU, ranging from 2.1% to 5.3% of national GDP.[2] Thus, preventing mental health issues by using proactive measures or by increasing the financial security of employees has huge potential to improve state finances.

The importance of mental health for life satisfaction

Using data from Australian, UK, and German households Layard, et al. were able to show that “Mental health is the biggest single predictor of life satisfaction. This is so in the UK, Germany and Australia… It explains more of the variance of life satisfaction in the population of a country than physical health does, and much more than unemployment and income do” (Layard, et al., 2013, p.1).

This underlines the tremendous effect that mental health has on the most important indicator for measuring quality of life. While, for example, unemployment doesn’t have the same strong effect on life satisfaction that mental health has, considering the detrimental effects that unemployment or financial insecurity has on mental health, it becomes obvious that the effects of economic insecurity and bad mental health, taken together, have on life satisfaction are quite devastating.

Precarity and financial insecurity: What do they mean?

A relatively new term that has been coined to describe these problems – at least for the more advanced welfare states in the Global North – is precarity (Standing, 2011). A problem with precarity is that it is difficult to quantify. According to Fong (2018), to operationalise precarity, researchers refer to the term “‘nonstandard work,’ which covers part-time, temporary and contract employment”. The problem with that categorisation is that it encompasses part-time employment, which might be explicitly desired, where people earn some extra income or well-off retirees keep busy. For this reason, economic insecurity is useful in describing the effects of automation on mental health. Bossert & D’ambrosio (2013, p. 5) provides another useful definition: “Economic insecurity is the anxiety produced by the possible exposure to adverse economic events and by the anticipation of the difficulty to recover from them”.[3]

State of the art mental health and precarity

There is vast literature on the correlation between unemployment and mental health, as well as other forms of precarity such as financial insecurity or the fear of losing one’s job (Burgard & Seelye 2016; László, et al., 2010; Llosa-Fernández, et al., 2018; Rajani et al., 2016; Rohde et al., 2016; Watson & Osberg, 2018). These researchers have all found a positive correlation between anxiety connected to job loss or financial insecurity and deteriorated mental health. While in the past decades research focused solely on unemployment and its negative consequences, more recently the fear of the fear – meaning the fear of losing one’s job – has gained more attention.

It turns out that this second-degree fear actually has a stronger negative effect on mental health than if the anticipated event (unemployment) actually materialises. This realisation is key, as the fear of social decline is central in all discussions about precarity in parts of the middle classes in Western welfare states. This perception of being at risk of social decline has contributed to the wave of political populism. Needless to say, people in lower socioeconomic classes have experienced precarity much longer and have thus been exposed to the negative effects of financial insecurity for longer. In a study by Hense (2018), individuals were more likely to perceive themselves as more precarious if they perceived a risk of losing their job. Generally, people perceive a higher degree of precariousness when their potential job loss would have more severe consequences on their lives and on their families (e.g., no cash buffer available).

The perception of precarity is higher in people who, because of their education or occupational status, have lower labour market opportunities or do not have a long-term employment perspective due to their fixed-term contracts. In line with previous research, Hense emphasised that perceiving one’s situation as precarious promotes illnesses, lowers subjective well-being, and leads to conflicts at work and in families. According to a representative survey in EU countries, a vast majority of employees (88%) feel some level of insecurity in their future prospects to land a similar job or to lose their current one (Dubois, Leončikas, & Hansen, 2018). Workers with permanent contracts are less likely to assume that they will have to look for a new job in the next 6 months (2%), while this number is eight times higher for workers with fixed-term contracts of 12 months or less (17%) (Dubois et al., 2018).

State-of-the-art automation and the Global South

There is a vast body of literature on how automation impacts countries in the Global North and South. Generally, it is thought that the Global South is more severely impacted by automation. First, rich countries have already outsourced the most easily automatable tasks or jobs to the Global South, where manufacturing jobs were growing until recently. It is possible that as robots become more advanced, production facilities might be reshored. Machines could then do most of the jobs in the mother countries’ factories (lights-out manufacturing). With rising labour costs in the Global South and advancing robot technology in the West, reshoring would help companies to save costs. Another intriguing argument is that, for example, 3-D printing makes it possible for specialised companies (or even customers themselves) to produce customised products close to their clients for a fraction of the current cost of production. This would entail a further reduction of manufacturing jobs in the Global South.

One of the major counterarguments is that robots will in many areas simply be too costly for emerging economies and therefore they will still have to rely on human labour force in the foreseeable future. Even if this is true in the short term, I believe that in the long term these countries will be more and more outcompeted by other countries in the Global South, where companies have the financial capabilities to complement or replace their human work force with machines on a larger scale. It is even possible that they will be competing against industrial goods from lights-out factories in the Global North that are able to produce goods more cheaply. Once the loans for the robots are paid off, only electricity, material, and maintenance costs occur. In contrast with humans, robots are able to work 24 hours a day with a low error rate and may thus quickly supersede their human counterparts in emerging economies.

In general, it is possible that automation will complement humans and enable them to delegate mundane and dangerous tasks to intelligent machines. This would give humans the opportunity to concentrate on more rewarding tasks. In addition, lower prices could spur demand and thus contribute to job creation. This is a possible scenario, but it needs serious political backing, which at this moment seems light years away in all of the major economies around the world.

UBI or cash-transfer-pilots and impact on mental health

Reviewing the literature on different sorts of cash transfers, there is evidence of beneficial impact of these policies on mental health.

One of the earliest pilots, called ‘Income maintenance’ (means-tested negative income tax), was conducted with about 1,400 households in three American states during the 1960s. While there were slightly positive impacts on, for example, graduation rates, no impact on health or psychological well-being was detected (Brown, 1988).

The Canadian ‘Mincome’ experiment was conducted between 1974 and 1979 in Dauphin, Manitoba, where 60% of the average national per capita income was given to low-income families and individuals. Among others, this scheme had a substantial impact on physical and mental well-being. Hospital visits dropped by 8.5%, with fewer incidents of work-related injuries, and fewer emergency room visits from accidents and injuries. Forget also “found that participant contacts with physicians declined, especially for mental health”” (Forget, 2011, p.1, emphasis added).

The Great Smoky Mountains Study of Youth began in 1993 in the southern Appalachian mountain region of North Carolina. For Native American youths, the results show that the cash transfer “effect reduces behavioural disorders by 26.7 % of a standard deviation” and “increases conscientiousness by 42.8 % of a standard deviation”, and parental drug and alcohol consumption were – as result of improved family relationships – reduced (Akee, Simeonova, Costello, & Copeland, 2015, p.38).

In a pilot project in Malawi, the outcome of a cash-transfer program was that 38% of school girls were less likely to suffer psychological distress, because the negative effects decreased with a rising transfer amount provided to the parents, conditional on regular school attendance. However, these positive effects were not detectable anymore after the cash transfer ended. (Baird, De Hoop, & Ozler, 2011).

A similar effect became visible in an income supplements project in Kenya, where “youth experienced 24% less depressive symptoms, psychological well-being increased and the benefits played a buffering effect for the mental health of orphaned children” (Shangani et al., 2017, p.8).

Most of the results from these pilot projects suggest that a cash-transfer program has strong positive effects on the psychological well-being of people in general and of the youth in particular.

According to recent survey results from a 2-year-long Finnish pilot on basic income, the recipients of basic income perceived their overall well-being as better compared to the control group.[4]In this study, 55% of the recipients of a basic income and 46% of the control group perceived their state of health as good or very good (Finnish Employment Agency [Kela], 2019). In addition, 17% of the recipients of a basic income and 25% of the control group experienced a high or very high degree of stress. Minna Ylikännö, the lead researcher at Kela, stated: “The recipients of a basic income had less stress symptoms as well as less difficulties to concentrate and less health problems than the control group. They were also more confident in their future and in their ability to influence societal issues”. (Finnish Employment Agency [Kela], 2019).

Although this result doesn’t explicitly mention mental well-being, it is fair to assume that an increase in people’s perceived health conditions by 9% and a decrease in stress levels by 8% would have a positive effect on mental health. Moreover, trust in other people and politicians increased by 5 percentage points. More financial stability led people to trust more in others. Trust, in turn, can be seen as a remedy to reduce stress, which has positive effects on mental health.

In summary, providing people with additional cash seems to have an overall very positive effect on mental well-being.

Supporters and opponents of UBI

When looking at the potential of certain social policies, it is important to understand which part of the constituency are in favour or against a certain policy. An opinion poll among 2,000 US citizens in 2017 showed that older age groups are less supportive of UBI. A trendline shows the positive correlation between growing age and increasing opposition to UBI. Younger age groups a usually more supportive of UBI.

Figure 4

The graph is based on data from Politico’s Morning Consult National Tracking Poll #170911, September 14–17, 2017. Retrieved from https://www.politico.com/f/?id=0000015e-9b5e-d7ac-a3fe-ff7f395a0001.

The European Social Survey from 2016comes to similar results. Generally, support for UBI declines with increasing age. Two notable exceptions are those aged 65 or older in Eastern Europe and the Christian Democratic Welfare states, where there is higher support for UBI than with those aged 55–64 years old Fitzgerald, Bottoni, & Swift (2017). European Social Survey 2016.

As we can see from the voter turnout from the United States , average voter turnout is increasing and reaches its climax at between the ages of 70 and 75 years. These people also tend to be less supportive of UBI (Franklin (2018). Age and voter turnout). As can be seen from the Brexit vote, where younger voters were more in favour of “remain,” the higher turnout of older voters decided the referendum in favour of Brexit. People promoting UBI should be aware of this age gap and the strong political support anti-UBI politicians could mobilise from older age groups. For UBI supporters, this means that they would have to successfully lobby for UBI among older voter groups. Alternatively, political decision makers have to be convinced that UBI is necessary for increasingly automated economies with fewer and fewer jobs, which will have a particularly strong impact on younger voters even though they don’t show up at the polls to the same extent as older voters. A more general problem of many political systems is that politicians tend to make short-term decisions, with the most important factor being getting re-elected after four or five years in government. With regard to the automation-related aspects, this problem becomes even more severe, since the pace of technological development is increasing quickly. That calls for a more visionary approach to safeguard the future and livelihoods of the present younger generation and not to pour too many resources and attention into the older age groups.

Financial insecurity and fear of death

In a market economy, not having enough money can be equated with “becoming more vulnerable to death. People go on holding money as a protection, although they know perfectly well that there is no way to protect yourself against death” (Osho, 2011, p. 134).

Cash or other resources are key in a market-driven economy because they provide the feeling of being protected against the consequences of a job loss and other financial turbulences. Generally, there are three types of welfare states. At the one end of the spectrum are liberal welfare states such as the United States, the UK, and Canada, and at the other end of the spectrum are the social-democratic welfare states, while conservative corporate welfare states are in the middle of the spectrum. It seems obvious that in other welfare states with less social protection, like the United States, the power of money or the fear of not having enough money is much more strongly developed than in other welfare states. On a macro level, one could thus reason that this stronger fear creates higher levels of mental unwell-being.

From a philosophical stance, as pointed out above, nothing can protect people from the ultimate source of all fears, which is the fear of death. The perceived protection of money from this fear, however, helps many people in their daily lifes. An economic buffer can thus be seen as a spacer between a person and the fear of losing everything. Research on economic security points out: “The basis for concern about economic security is the belief that uncertain economic prospects leave people worse off. This belief has two logical foundations: that individuals fear large economic losses; and that when individuals experience such losses without sufficient buffering, they suffer hardship, particularly (but not only) if those losses are unexpected” (Hacker et al., 2013, p. 4).

Looking at IHME data on healthy years lost due to mental illness per 100,000 inhabitants and household debt as percentage of household net income I find a positive correlation between these two measures. An increase of household debt by 1% would result in a loss of two years of healthy life per 100,000 inhabitants (0.007 day for one person). An increase of debt by 100% would lead to a loss of 0.73 days of healthy life for one person. Decision makers should keep in mind that policies that result in increased household debt have a direct negative impact on quality of life in a medical way, effectively shortening people’s healthy lives. This insight is especially crucial in a time were neoliberal austerity policies are part of the political mainstream all over the globe. Neoliberal policies not only widen the gap between rich and poor, but they also shorten the years of healthy life of the poor in particular. In this sense, it is very likely that events that increase financial insecurity have a negative impact on mental health.

Involuntary part-time employment and mental health

Neoliberal policies and economic crises are one of the main driving factors for an increase in part-time work.

Figure 6

Note: Chart is based on data from Eurostat http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_eppgai&lang=en

The chart above shows that in all countries the share of people working in involuntary part-time employment has increased. For 7 out of 21 countries, a sharp increase can be witnessed starting from the base year 2008, which is when the economic crisis hit. For a majority of countries, the number of people in involuntary part-time work is higher than in the base year 2008. This is an additional illustration of how a financial crisis impacts the job market negatively. When taking into account the positive correlation between mental health and involuntary part-time employment, it becomes clear that economic hardship reflected in too few jobs or insecure jobs could be a threat to overall mental health.

Analysing data for the level of mental health issues and the percentage of people that are in involuntarily part-time employment (meaning they actually want to get a full-time position but aren’t able to), it turns out that there is a positive correlation between these two. A rise of 1 percentage point in the share of people in involuntary part-time work results in 3.44 years of healthy life lost due to mental illness per 100,000 inhabitants. For an individual person, a 10-percentage-point rise in involuntary part-time work results in 0.12 days of healthy life lost due to mental disorders.

Welfare, employment, and precarity

The softening of labour laws in the Global North, the weakening of trade unions representation and bargaining power, the outsourcing of manual jobs to the Global South, and the decreasing redistribution of financial resources in the social system (decreased wealth, inheritance, and corporate taxes) in the Global North has led to tremendous inequality and stagnating living standards among the lower classes and parts of the middle class. Neoliberal politics have watered down social policies and safety nets in the Global North. A big part of today’s precariousness and one’s own perception of precariousness derives from these policies. In the Global South, the situation is even more dramatic. In many countries of the Global South, the bigger part of value adding is performed in the informal economy, where the majority of workers is employed (often without written contracts). The International Labour Organization (ILO) states that 60% of workers work in the informal economy (ILO, 2018), with an associated low level of social protection.

Why is it important to talk about automation and precariousness? Although conditions differ between Global North and South, what both have in common is that automation-induced employment loss will stand for a bigger part of future precariousness. Whereas, in earlier times, neoliberal policies were one of the most important reasons for precariousness, in the future, the rate of automation-induced precarity will rise if the current economic system is not changed. Mental health issues will increase from an already high level among all age groups. Involuntary part-time work is part of precarity and financial insecurity and seems to have a detrimental effect on mental health. These factors, along with others such as the endless need for reskilling and continuous training, will contribute to the deterioration of mental health. The proven and tested model of deriving income from employment has to be revisited in Global South and North alike. In addition, welfare states will have to reconsider their approach to link payment of benefits to an individual’s contributions to the welfare system. Companies exist in a competitive market environment. Their task is to increase profits and to channel them to shareholders. Generally, it is not their aim to come up with job-creation or job-protection schemes. Therefore, it is naïve to believe that people whose work has been automated will be simply given more qualified tasks in the same company or that they will be retrained to get an equally good job elsewhere.

All of this opens deeply political concerns that relate to ownership of artificial intelligence (AI) and the overall question of who will reap the benefits of technological progress. In countries with strong welfare policies and good protection for employees, automation on par with other factors will probably undermine the welfare state, because digitalisation under neoliberal conditions is decreasing the number well-paying jobs for the masses. Ultimately, the rise in inequality will be further exacerbated by technology if not regulated properly.

Considering the public sector, job-protection programs would be an option. The fundamental questions: Is it desirable to keep people busy with tasks they may or may not feel content with, when there is an opportunity to let people allocate their talents and time resources according to their individual and their communities’ needs? Governments and companies as well as civil society organisations around the globe have to rethink their approaches to dependent employment as the major source of individual and family income.

Reskilling, stress, and financial insecurity and the deterioration of mental health

Lifelong learning is promoted as a panacea against automation-induced joblessness across party lines. This sounds like a logical conclusion. Knowledge and skills are becoming more and more complex across all professions. The level of knowledge and skills of workers has to be increased in line with the ever-evolving requirements of the labour market. Lifelong learning thus becomes the key ingredient to ensure employability. Continuous retraining will raise skill levels. While this is a valuable assumption in the short to midterm, thinking about technology and its potential impact in the long term (20–30 years) might lead to a different conclusion. Policymakers should have in mind that technological change accelerated by AI will operate at great pace.

While there is disagreement about whether technological progress will create more jobs then it destroys, there is unity among researchers that there will be a large shift in job profiles, resulting in a tremendous need for fast reskilling and further education.[5] When governments request lifelong learning and continuous reskilling from employees in order to be employable, this could lead to a “race against the machines”, where humans ultimately lose out to AI (Brynjolfsson, E., & McAfee, A. (2012). This is especially true for people who are not able (because of disabilities, sickness etc.) or don’t want to reskill on a continuous basis. The basic question arises to what degree humans want to accustom technological change and whether there is a saturation level where humans should not have to adapt to technology any more. Sooner or later, policymakers will have to become accustomed to the idea that the labour market as we know it today will increasingly be out of reach for the masses in the next decades.

I argue that it is wrong to shift all of the costs for reskilling to individual employees. Reskilling should be an active choice made by an employee. So rather than employees being forced to reskill, they should be empowered to make this choice out of their own free will. Therefore, the financial costs of adaptation resulting from the interaction of AI and humans should be entirely born by AI itself. The reasoning behind this is that as AI will be standing for the larger part of productivity gains, which will ultimately translate into increased profits for companies producing and deploying this technology. Only when sharing these profits among all people can a fair redistribution be guaranteed. A robot tax is an example of this kind of policy. In countries with a functioning welfare state, the government should contribute financially to reskilling. Further training should be embedded in all jobs in the private and public sector, and employees opting for it should be rewarded for this choice. Social systems and employer entities have to be geared to regard further training as if it would be part of regular employment with all the resulting benefits (sick time benefits, parental leave, etc.) as well as contributions (pensions, etc.). Retraining has to become part of every job on a regular basis.

However, reskilling measures born out of pure necessity, anxiety, or sanctions will greatly enhance the psychological pressure that labour market participants feel. As evident today, 88% of employees in the EU feel somewhat insecure with regard to their job security and/or their future employability. As the half-life time of knowledge keeps decreasing, the pressure for reskilling will continue to rise. Specialists in IT (information technology) have to learn a new programming language every 2 years just to keep up to date. While IT is, of course, a field characterised by a high pace of progress, it is likely that many other sectors will see a fast-changing set of skill requirements as well.

Pressure to adapt one’s skill level to ever rising skill standards will consequently produce anxiety and unease, especially in vulnerable groups that don’t have adequate resources. In the current economic market setting, that rising pressure to retrain and to reskill oneself is for many people born out of pure necessity to keep their job and pay the bills. This will inevitably lead to decreased mental well-being among all age groups. Also, people who are not participating in the labour market, for example, children and elderly people, will be affected by these changes, as families often heavily depend on working middle-aged people to provide for the whole family.

Are young people particularly affected by poor mental health caused by automation?

A literature review of several studies on youth mental health brings to light that a majority of surveys sees an uptick of mental health problems, in particular among young girls. A sharp increase in “psychological distress, major depression or suicidal thoughts, and more attempted suicide” has been witnessed among U.S. youths in 2011 (Twenge, Cooper, Joiner, Duffy, & Binau, 2019, p. 1). The reason behind this is not associated with the fear of not getting a job, but more with the extensive use of social media and cyber-mobbing and other online resources. In a recent online survey conducted among 4,600 adults by YouGov in the UK on how often people feel stress, it was found that “30% of older people reported never feeling overwhelmed or unable to cope in the past year compared to 7% of young adults.” In addition, 49% of the 18- to 24-year-old respondents “who have experienced high levels of stress felt that comparing themselves to others was a source of stress, which was higher than in any of the older age groups” (Mental Health Foundation, 2018). Approximately half of the people who felt stressed reported feeling also depressed or anxious.

In another study from the UK, researchers questioned young social media users about their social media usage and how it impacts their inner world. Besides the positive effects that the usage of some of the social media platforms have, photo-driven platforms like Snapchat and Instagram had more negative than positive effects. “Seeing friends constantly on holiday or enjoying nights out can make young people feel like they are missing out while others enjoy life. These feelings can promote a ‘compare and despair’ attitude in young people” (Inkster, 2018, p.8).

In a study among 753 high school students in Canada, a correlation between social media usage and mental health was found. “Daily (social media) use of more than 2 hours was also independently associated with poor self-rating of mental health and experiences of high levels of psychological distress and suicidal ideation. The findings suggest that students with poor mental health may be greater users of social media” (Sampasa-Kanyinga & Lewis, 2015, p. 1).

It thus seems that youths are not under a bigger risk of deteriorated mental well-being caused by automation. Although today almost half of the young people in Germany are employed in working conditions that would qualify as precarious (less than 20 hours per week, temporary employment, and contract work), this doesn’t necessarily mean that these people perceive their employment as precarious; it may be important to them to earn some additional income and pursue their training. The perception and conscious acknowledgement of being in a precarious condition makes people feel worse and impacts mental health negatively. Finding oneself in an objectively precarious working situation but not perceiving it as precarious probably has no impact on mental health. Thus, perceptions are related to the framework of references people have. Growing up in an economic system and labour market characterised by neoliberal policies, such as cutting back the welfare state and employment rights, today’s youth are eventually more accepting of the present precarious labour market as their frame of reference lacks the experience of unlimited employment contracts and the successful labour struggles of workers in the past. Allegri et al. coined the term “precarious natives” (Allegri, et al. 2018, p. 57) for young people between the ages of 18 and 35, “those who were born and raised in precarity and the (financial) crisis, and find themselves fully immersed in the dimension of the ‘odd jobs’ first and the gig economy later. They seem to have a more disenchanted and less ‘ideological,’ more pragmatic relationship with work” (Allegri, et al., 2018, p. 57). Their pragmatic view of the precarious labour market perhaps makes it easier for them to adapt to their current situation.

Nevertheless, while growing older and earning a degree or attaining a trade, these people probably will not enjoy the benefits of the previous generation of stable, long-term employment in the Global North as mini-jobs and contract work have decreased the total number of jobs subject to social security contribution. To build a family or to earn more money for better health care or to upgrade one’s lifestyle will not be possible under the current labour market situation and economic policy. Therefore, the growing need for more financial means in older age and fewer opportunities than previous generations to buy property will affect their mental health negatively.

In the past two decades a deterioration of working conditions has taken place. In Germany, permanent full-time employment with all its associated benefits (pension contribution, unemployment insurance, paid vacations, etc.) decreased by 10 percentage points while precarious mini-jobs and self-employment increased by 8 and 2 percentage points between 1991 to 2017.

What we have to keep in mind is, though, that mental health has to be accessed over longer periods of time as it improves or deteriorates, usually not related to a single event (an exception is the sharp rise in mental health disorders after 2011 among young people in the US). Rohde, et al. (2016) stated “for the average individual the negative health effects of economic insecurity are unlikely to greatly affect their mental health status in a single specific year. Indeed, several shocks are required to make a clinically important difference, and at least 10 are required to make an otherwise average person mentally unwell” (Rohde, et al., 2016, p. 255). Mental health disorders contracted during a young age might have a profound on well-being and labour market integration at an adult age.

All in all, if the current economic policy is not changed, precarious work arrangements will become even more widespread in the Global North, on par with increased automation, and thus penalise workers, especially younger people. Young people usually start to work on fixed-term employment contracts, which can help them to get a foot into the labour market. At the same time, we are witnessing the development in the Global North of fixed-term contracts becoming endemic. This might be justifiable for recent graduates, but most likely fixed-term contracts will accompany these people through a substantial part of their adult life. Therefore, if social policies are not adjusted to address above-mentioned problems, the mental health of youth will further deteriorate, this time due to automation-induced job loss.

UBI in the Global North and South

In emerging economies, where welfare measures are at a relatively formative stage (not covering living costs), the gradual introduction of some form of cash transfer or UBI promises to help reduce poverty. Increasing wealth concentration in emerging countries (e.g., India’s richest 1% own 58% of national assets) points to an urgent need for equality-inducing distributive mechanisms (India’s Rising Income, 2017). The risk of job automation is higher in emerging economies than in wealthy countries. Therefore, technological progress could have much more dire consequences for the labour markets there and leave more employees and their families without sufficient income. This makes the argument for an introduction of cash transfers or UBI stronger for countries of the Global South.

For advanced economies with more established social policies, a reform agenda focusing on improvements of existing structures addressing the negative effects of income and wealth concentration is preferable. Important and well-functioning social policies and institutions should be preserved, but changes are necessary. Governments should reaccess the traditional model of linking social benefits to employed work, as job opportunities will probably decrease in the future, while skill requirements will rise at a fast pace. To reform the welfare state, different kinds of social policies have to be adopted to fit new realities. Only after such steps have been taken and reviewed – and once recently started UBI experiments have been evaluated – will it make sense to discuss the necessity of extensive measures such as UBI.

UBI as a means to improve mental health?

A holistic set of measures has to be applied to counter the negative developments induced by neoliberal policies and the detrimental effect of technological progress substituting capital for labour in a neoliberal context. As mentioned above, UBI can be a valuable tool, in particular in the Global South. Financial problems stand for a substantial part of (detrimental) stress that in turn causes mental disorders. To spur real and sustainable improvement of people’s mental health, the following have to go hand in hand: expanded welfare policies; promoting employment rights; fair taxation of transnational corporations and tech companies; better access to high-quality education, child care, and further job training; decent (as well as safe) retirement schemes for all professions; affordable and good-quality health care; taxation of robots and AI; finance and transaction tax; and measures to protect the environment to decrease CO2 emissions.

A big advantage of UBI is that it would immediately wipe out all of the distress that is caused by the fear of potentially not having enough money to pay one’s monthly bills. It would also substantially decrease all of the fears that are associated with the physical workplace (such as being afraid of the boss or co-workers, etc.). The majority of the relatively few pilot projects on cash transfers and UBI have shown that regular access to more financial resources for vulnerable groups has a great potential to seriously improve mental health.

With regard to future employment in the wake of technological progress, UBI could be an important cornerstone. People would still have the legitimate fear that an intelligent machine might replace them, but at least they would be sure to have an unconditional basic income that would provide them with the necessities of life. Moreover, mental stress caused by the constant need to adjust to the labour market and to engage in reskilling might be diminished with a stable flow of income.

Generally, more time to engage in social relations with family, friends, and community might also improve overall well-being and thus mental health. Also, wealthier social groups would – despite their loss of financial income – benefit from an overall improved social climate.

The standout question is that of political feasibility, given UBI’s redistributive nature. In political systems, where parliamentary decisions are biased in favour of the wealthy parts of population, supportive parliamentary majorities for redistributions would seem to be unlikely. There is some evidence (e.g., for Germany, Elsässer, Hense, & Schäfer 2017), that political decisions are more in line with the interest of wealthier social groups especially where interests of rich and poor are colliding. Advocates of UBI have to be aware of this. It would thus be important to show how the wealthier group – despite a loss of income – would benefit in other ways from UBI.

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[2] The amount spent on mental health problems doesn’t necessarily reflect the actual urgency of mental issues in a particular country. It could be that some countries are more advanced in detecting mental health issues. In addition, some countries could simply be spending more on mental health, because they have comprehensive and (costly) treatment to offer their population, which could be a good thing.

[3] Another interesting definition is included in Rohde et al.’s (2016) proxy indicator for job insecurity. In their view, the most predictive measures for mental distress in the subset of this indicator are “job insecurity, probability of experiencing expenditure distress, and lacking access to emergency funds” (Rohde et al., 2016, p. 255)

[4] This study included only unemployed people between 24 and 58 years, all of whom had to take part in the experiment.

[5] Measures have to be taken to either create a human-friendly AI (that complements humans), an AI that is superior to humans, but that is under tight human control, or a neo-Luddistic (technophobic) society that refrains from the most advanced technologies for reasons of control and more human interaction. The fourth and least favourable option would be a human society that is policed by AI.

Klemens Witte, Research Associate at the DOC, is specifically interested in economic questions, international relations, and policy-making.
He holds a Masters in Political Science and Intercultural Communication (Martin-Luther-University Halle-Wittenberg), a second Masters in Baltic Sea Studies (Södertörns University College/Stockholm), and a postgraduate LL.M. in International Economic Law (Southwest-University for Political Science and Law/Chongqing and Martin-Luther-University Halle-Wittenberg).
Klemens Witte has gained international experience in universities in Kazan, Moscow, Kaliningrad, Minsk, and Beijing. He has further work experience within the fields of internationalization and education as a desk officer with Swedish government ministries and as a lecturer from the Moscow State Institute of International Relations. He speaks German, English, Swedish, Russian, and Chinese.